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Powerfully Simple Trade Promotion Optimization

Promotions, advertising and other forms of “demand shaping” can be enormously expensive, costing more than 15% of gross revenues. Yet determining their actual impact or “lift” remains a daunting problem. A large number of variables with complex interactions are buried in huge amounts of data with a high degree of noise. Even with substantial expertise and fairly consistent baseline demand, it’s usually not possible to understand correlations among variables.

To solve this problem, we turned to a powerful machine learning technology called Rulex®. This technique recognizes the shared characteristics of promotional events and identifies their effect on normal sales. It extracts knowledge about which variables most impact demand and produces a set of simple intelligible rules, easily understood by the user. Fast multi-dimensional modelling handles both qualitative and quantitative variables. It can also handle unstructured or partial data.

Our customers are deploying machine learning-based analytics for applications such as:

  • Media events forecasting, to optimize spend and reduce lost sales and stock-outs
  • Promotion and social media optimization, to identify the promotions that consumers want and maximize margin return on marketing spend
  • Leveraging web data (such as page views and bounce rates) to predict which new product introductions will become ‘the stars’
  • Customer segmentation clustering to understand the complex behavioural patterns of each customer segment

This breakthrough technique creates a major improvement in demand visibility, forecast quality and level of demand modeling.

Read Case Study Promotion and Media Forecasting
Read Case Study Supply Chain Planning with Heavy Promotional Influence
Watch Video Three Reasons Why Trade Promotion Forecasting is Difficult


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